class_docstr: Contains unit tests for the TransportNNDistanceComputer class. 
docstr: Tests distance computation for a single connectivity coefficient. 
docstr_tok: ["Tests","distance","computation","for","a","single","connectivity","coefficient","."]
code: def _test_dist_comp_for_multiple_coeffs(
      self, nns, dist_types, mislabel_coeffs, struct_coeffs, tp_comp
  ):
      """Tests distance computation for a single connectivity coefficient."""
      num_nns = len(nns)
      for i in range(num_nns):
          for j in range(i, num_nns):
              nn_i = nns[i]
              nn_j = nns[j]
              dists = {}
              for dt in dist_types:
                  dists[dt] = tp_comp(
                      nn_i,
                      nn_j,
                      dist_type=dt,
                      mislabel_coeffs=mislabel_coeffs,
                      struct_coeffs=struct_coeffs,
                  )
                  num_dists = len(dt.split("-")) * len(mislabel_coeffs)
                  assert len(dists[dt]) == num_dists
              res_str = " ".join(
                  [
                      "%s=%s"
                      % (
                          self._get_dist_type_abbr(key),
                          get_list_of_floats_as_str(val),
                      )
                      for key, val in dists.items()
                  ]
              )
              self.report(
                  "(i,j)=(%d,%d) %s" % (i, j, res_str), "test_result"
              )
  
imports: import numpy
  from .None import otmann
  from .unittest_neural_network import generate_cnn_architectures, generate_mlp_architectures
  from ..utils.ancillary_utils import get_list_of_floats_as_str
  from ..utils.base_test_class import BaseTestClass, execute_tests
label_desc: Use image node_id 11 for calling the TransportNNDistanceComputerTestCase obj's underlying member method code with example usage: obj._test_dist_comp_for_multiple_coeffs(nns, dist_types, mislabel_coeffs, struct_coeffs, tp_comp) without return types